Development Of A Fire Detection System On Satellite Images
Sergey Yarushev, Alexey Averkin

TL;DR
This paper presents a deep neural network architecture for wildfire detection in satellite images and explores its application in macroeconomic forecasting using fuzzy cognitive maps.
Contribution
It introduces a convolutional neural network for wildfire recognition and integrates it with fuzzy cognitive maps for macroeconomic analysis.
Findings
Effective wildfire detection on satellite imagery.
Potential for macroeconomic forecasting using wildfire data.
Integration of deep learning with cognitive maps for economic analysis.
Abstract
This paper discusses the development of a convolutional architecture of a deep neural network for the recognition of wildfires on satellite images. Based on the results of image classification, a fuzzy cognitive map of the analysis of the macroeconomic situation was built. The paper also considers the prospect of using hybrid cognitive models for forecasting macroeconomic indicators based on fuzzy cognitive maps using data on recognized wildfires on satellite images.
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Taxonomy
TopicsCognitive Science and Mapping · Environmental Sustainability and Technology
